collaborators

5 papers

physics.chem-ph2026

AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms

Emmanuel Bengio, Sanjeev Raja, Yui Tik Pang +5

We present AquaGen, the first all-atom, explicit solvent, periodic-boundary-condition-aware generative model that produces molecular configurations from the Boltzmann distribution…

cs.LG2026

MarS-FM: Generative Modeling of Molecular Dynamics via Markov State Models

Kacper Kapuśniak, Cristian Gabellini, Michael Bronstein +2

Molecular Dynamics (MD) is a powerful computational microscope for probing protein functions. However, the need for fine-grained integration and the long timescales of biomolecular…

cs.LG2026

Relaxed Equivariance via Multitask Learning

Ahmed A. Elhag, T. Konstantin Rusch, Francesco Di Giovanni +1

Incorporating equivariance as an inductive bias into deep learning architectures to take advantage of the data symmetry has been successful in multiple applications, such as chemis…

cs.LG2025

A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition

Nian Liu, Xiaoxin He, Thomas Laurent +3

Spectral graph convolution, an important tool of data filtering on graphs, relies on two essential decisions: selecting spectral bases for signal transformation and parameterizing…

cs.LG2025

Understanding Virtual Nodes: Oversquashing and Node Heterogeneity

Joshua Southern, Francesco Di Giovanni, Michael Bronstein +1

While message passing neural networks (MPNNs) have convincing success in a range of applications, they exhibit limitations such as the oversquashing problem and their inability to…